Fast Simulated Annealing with Greedy Selection

A greedy gradient-simulated annealing selection hyper-heuristic

Educational timetabling problem is a challenging real world problem which has been of interest to many researchers and practitioners. There are many variants of this problem which mainly require scheduling of events and resources under various constraints. In this study, a curriculum based course timetabling problem at Yeditepe University is described and an iterative selection hyper-heuristic ...

Fast Simulated Re - Annealing

An algorithm is developed to statistically find the best global fit of a nonlinear non-convex cost-function over a D-dimensional space. It is argued that this algorithm permits an annealing schedule for ''temperature'' T decreasing exponentially in annealing-time k, T = T 0 exp(−ck 1/D). The introduction of re-annealing also permits adaptation to changing sensitivities in the multi-dimensional ...

Very Fast Simulated Re-Annealing

A Fast Algorithm for Simulated Annealing

We present a new deterministic algorithm for simulated annealing and demonstrate its applicability with several classical examples: the ground state energies of the 2d and 3d short range king spin glasses, the traveling salesman problem, and pattern recognition in computer vision. Our algorithm is based on a microcanonical Monte Carlo method and is shown to be a powerful tool for the analysis o...

Simulated annealing for supervised gene selection

Genomic data, and more generally biomedical data, are often characterized by high dimensionality. An input selection procedure can attain the two objectives of highlighting the relevant variables (genes) and possibly improving classification results. In this paper, we propose a wrapper approach to gene selection in classification of gene expression data using Simulated Annealing along with supe...